Responsibilities
- End-to-End Prototyping Build cross-stack prototypes using ATLAS AI, CDF, and open-source AI frameworks to solve real customer challenges.
- Agent Workflow Design Design and implement multi-agent workflows that combine LLMs, tool use, and reasoning over industrial data.
- Tech Exploration & Integration Evaluate and integrate new GenAI tools, open-source frameworks, and APIs into ATLAS AI workflows.
- System Optimization Benchmark performance, tune retrieval and reasoning pipelines, and ensure scalability in real-world industrial deployments.
- Collaboration & Co-Innovation Work with solution engineers and customer teams to align models and agent behaviors with business value and industrial constraints.
What We’re Looking For - Must-Have Skills
- 5+ years of experience in AI/ML engineering, with hands-on delivery of models.
- Proficiency in working with foundation models (LLMs), including :Prompt engineering, evaluation, and (when relevant) fine-tuning.
- RAG pipelines and integration with knowledge bases or vector databases.
- Strong Python skills with experience using frameworks such as LangChain, Transformers, or similar.
- Understanding of cloud-native development, model training workflows, and ML pipeline orchestration (e.g., data labeling, feature selection, model retraining).
- Proven ability to write clean, maintainable, and scalable code, following engineering best practices for testing, version control, and review.
- A maker mindset with bias toward rapid iteration, showing rather than telling, and learning by doing.
Bonus Skills
- Experience with Cognite Data Fusion (CDF).
- Experience integrating AI workflows with time series, asset hierarchies, or knowledge graphs.
- Deep learning or traditional ML background (e.g., model architecture selection, hyperparameter tuning, evaluation pipelines).
- Understanding of industrial data types (e.g., time series, contextual events, industrial knowledge graphs).
- Experience labeling industrial datasets, including annotation strategies and working with imperfect or sparse labels.
Top Skills
What We Do
Cognite is an AI company that delivers industrial software to improve the production efficiency of Energy, Process Manufacturing, and other industrial companies.
We deliver an Industrial DataOps platform that liberates siloed data and empowers our customers to solve some of their most complex business problems with AI-powered solutions. The typical solutions we enable drive innovative new ways to approach Data Exploration, Digital Operator Rounds, Production Optimization, Turnaround Planning, and Root Cause Analysis.
We do this by automating and scaling industrial data contextualization of various sources (such as time series, engineering diagrams, equipment logs, maintenance records, 3D facility models, images, large point clouds, and more). We use AI and other tools to find and map the meaningful relationships between the data across these various sources. In addition, we provide intuitive tools that enable efficient use of analytics and automated workflows, as well as prebuilt AI capabilities and a low-code industrial agent builder, Cognite Atlas AI, that enables AI to carry out more complex operations with greater accuracy.
Why Work With Us
Employees at Cognite are pushing the envelope with the latest cloud technology, scaling industrial applications across hundreds of assets, revolutionizing industrial data models, and working with robotics. Cogniters are fast, creative, and resilient. We keep the energy high and fun, learning from our mistakes and celebrating our victories together.
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